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GeneSpeak-FP model retrieves drug targets from cell responses

By PulseAugur Editorial · [1 sources] ·

Researchers have developed GeneSpeak-FP, a Transformer-based retrieval model designed to identify potential drug targets and compounds from cell-level transcriptional responses. The model analyzes perturbation signatures, comparing treated cells to a DMSO reference, to generate vectors for target and molecular embedding. Evaluated on the Tahoe-100M dataset, GeneSpeak-FP achieved promising results in a closed-library setting, demonstrating its capability to recover both target annotations and compound identities. AI

IMPACT This model could accelerate drug discovery by enabling faster identification of potential targets and compounds from biological data.

RANK_REASON The cluster contains a research paper detailing a new model for biological data analysis. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

GeneSpeak-FP model retrieves drug targets from cell responses

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The cluster contains a research paper detailing a new model for biological data analysis. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Kseniia Vaniushkina, Jeongmin Lim, Jinyong Park ·

    GeneSpeak-FP: Target and Compound Retrieval from Observed Cell-Level Perturbation Signatures

    arXiv:2607.17671v1 Announce Type: new Abstract: Large-scale single-cell perturbation atlases make it possible to ask an inverse question: given an observed transcriptional response, which annotated targets and compounds in a fixed library are most consistent with that response? W…

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